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netcafe-live-data

by com.ainetcafe

Look up a package (npm / PyPI / crates / Go)

package_info
Read-onlyIdempotent

Latest version, license, repo, description, dependencies and weekly downloads for any public package. Use it before adding a dependency, or to check whether the version in a lockfile is current.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesPackage name, e.g. "react", "requests", "serde", "github.com/gin-gonic/gin".
ecosystemNonpm (default) | pypi | crates | go

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is known. The description adds valuable context about the scope ('any public package') and the kind of data returned, which goes beyond what annotations provide. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences long, front-loaded with the primary action and key output fields. Every word serves a purpose, with no fluff or repetition of schema details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the low parameter count (2), full schema coverage, and presence of an output schema, the description is complete. It lists the main returned fields and gives practical usage context, so an agent has a full picture of what the tool does.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% for both parameters (name and ecosystem), so the schema already documents the parameters effectively. The description adds minimal parameter-specific meaning, but the baseline of 3 applies because no additional clarification is needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Look up a package') and lists specific returned data fields (version, license, repo, description, dependencies, weekly downloads). This distinguishes it from sibling tools like ip_lookup or ssl_check, which focus on different domains.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit use cases: 'Use it before adding a dependency, or to check whether the version in a lockfile is current.' It does not mention when to avoid using it or name alternatives, but the context is clear enough for an agent to decide.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All netcafe-live-data toolsInspect
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TDQS

A3.6/5.0
Disambiguation4/5

Most tools are clearly separated by domain, but the cluster of domain-related tools (domain_check, ssl_check, china_reachability) could be confused by an agent looking for a generic 'check this domain' operation. The descriptions help clarify each one's specific focus, so overall ambiguity is low.

Naming Consistency2/5

Naming conventions are mixed: some tools use a verb-first pattern (check_vulns, get_weather, transpile_sql), while others use a noun-first pattern (domain_check, stock_quote, ip_lookup). Verbs are also inconsistent (check, get, lookup, transpile), and some names are pure noun phrases (exchange_rate, package_info). This lack of a uniform pattern makes the set feel disjointed.

Tool Count4/5

At 11 tools, the count is within a reasonable range and each tool has a distinct purpose. The broad scope makes the set feel somewhat unfocused, but there is no redundancy or excessive bloat.

Completeness3/5

The server intends to provide live data, but coverage is shallow within each category. For example, weather only gives current conditions and a short forecast, package tools only have info and vulnerabilities, and there is no historical data for stocks. The overall domain is vague, so significant gaps exist for a general-purpose live-data server.

Resources